{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T12:40:43Z","timestamp":1760186443968,"version":"build-2065373602"},"reference-count":35,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2019,1,16]],"date-time":"2019-01-16T00:00:00Z","timestamp":1547596800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the National Key Research and Development Program of China","award":["2016YFB0700500"],"award-info":[{"award-number":["2016YFB0700500"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>Image registration is an important process in image processing which is used to improve the performance of computer vision related tasks. In this paper, a novel self-registration method, namely symmetric face normalization (SFN) algorithm, is proposed. There are three contributions in this paper. Firstly, a self-normalization algorithm for face images is proposed, which normalizes a face image to be reflection symmetric horizontally. It has the advantage that no face model needs to be built, which is always severely time-consuming. Moreover, it can be considered as a pre-processing procedure which greatly decreases the parameters needed to be adjusted. Secondly, an iterative algorithm is designed to solve the self-normalization algorithm. Finally, SFN is applied to the between-image alignment problem, which results in the symmetric face alignment (SFA) algorithm. Experiments performed on face databases show that the accuracy of SFN is higher than 0.95 when the translation on the x-axis is lower than 15 pixels, or the rotation angle is lower than 18\u00b0. Moreover, the proposed SFA outperforms the state-of-the-art between-image alignment algorithm in efficiency (about four times) without loss of accuracy.<\/jats:p>","DOI":"10.3390\/sym11010096","type":"journal-article","created":{"date-parts":[[2019,1,17]],"date-time":"2019-01-17T11:30:27Z","timestamp":1547724627000},"page":"96","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Symmetric Face Normalization"],"prefix":"10.3390","volume":"11","author":[{"given":"Ya","family":"Su","sequence":"first","affiliation":[{"name":"School of Computer and Communication Engineering, University of Science and Technology Beijing, Xueyuan Road 30, Haidian District, Beijing 100083, China"},{"name":"Beijing Key Laboratory of Knowledge Engineering for Materials Science, Xueyuan Road 30, Haidian District, Beijing 100083, China"}]},{"given":"Zhe","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Computer and Communication Engineering, University of Science and Technology Beijing, Xueyuan Road 30, Haidian District, Beijing 100083, China"},{"name":"Beijing Key Laboratory of Knowledge Engineering for Materials Science, Xueyuan Road 30, Haidian District, Beijing 100083, China"}]},{"given":"Xiaojuan","family":"Ban","sequence":"additional","affiliation":[{"name":"School of Computer and Communication Engineering, University of Science and Technology Beijing, Xueyuan Road 30, Haidian District, Beijing 100083, China"},{"name":"Beijing Key Laboratory of Knowledge Engineering for Materials Science, Xueyuan Road 30, Haidian District, Beijing 100083, China"}]}],"member":"1968","published-online":{"date-parts":[[2019,1,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Cootes, T.F., Edwards, G.J., and Taylor, C.J. (1998, January 2\u20136). Active Appearance Models. Proceedings of the European Conference on Computer Vision, Freiburg, Germany.","DOI":"10.1007\/BFb0054760"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1109\/TSMCC.2009.2035631","article-title":"A Review of Active Appearance Models","volume":"40","author":"Gao","year":"2010","journal-title":"IEEE Trans. Syst. Man Cybern. Part C Appl. Rev."},{"key":"ref_3","unstructured":"Wan, J., Ren, X., and Hu, G. (2004, January 10\u201313). Automatic red-eyes detection based on AAM. Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, The Hague, The Netherlands."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1576","DOI":"10.1016\/j.sigpro.2009.02.008","article-title":"A new approach for face recognition by sketches in photos","volume":"89","author":"Xiao","year":"2009","journal-title":"Signal Process."},{"key":"ref_5","unstructured":"Stegmann, M.B. (, January July). Object tracking using active appearance models. Proceedings of the Danish Conference on Pattern Recognition and Image Analysis, Copenhagen, Denmark. Available online: http:\/\/www2.imm.dtu.dk\/pubdb\/views\/publication_details.php?id=115."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1109\/TSMCC.2007.913886","article-title":"Gait Components and Their Application to Gender Recognition","volume":"38","author":"Li","year":"2008","journal-title":"IEEE Transa. Syst. Man Cybern. Part C Appl. Rev."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"415","DOI":"10.1109\/42.925294","article-title":"Multistage hybrid active appearance model matching: Segmentation of left and right ventricles in cardiac MR images","volume":"20","author":"Mitchell","year":"2001","journal-title":"IEEE Trans. Med. Imaging"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1007\/s11263-013-0667-3","article-title":"Face alignment by explicit shape regression","volume":"107","author":"Cao","year":"2014","journal-title":"Int. J. Comput. Vis."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Kazemi, V., and Sullivan, J. (2014, January 23\u201328). One millisecond face alignment with an ensemble of regression trees. Proceedings of the Computer Vision and Pattern Recognition, Columbus, OH, USA.","DOI":"10.1109\/CVPR.2014.241"},{"key":"ref_10","first-page":"57","article-title":"Robust facial landmark detection via recurrent attentive-refinement networks","volume":"Volume 9905","author":"Xiao","year":"2016","journal-title":"European Conference on Computer Vision"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"427","DOI":"10.1016\/j.imavis.2015.11.004","article-title":"Approaching human level facial landmark localization by deep learning","volume":"47","author":"Fan","year":"2016","journal-title":"Image Vis. Comput."},{"key":"ref_12","first-page":"616","article-title":"Two-stage convolutional part heatmap regression for the 1st 3D face alignment in the wild (3DFAW) challenge","volume":"Volume 9914","author":"Bulat","year":"2016","journal-title":"European Conference on Computer Vision"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Trigeorgis, G., Snape, P., Nicolaou, M.A., Antonakos, E., and Zafeiriou, S. (2016, January 27\u201330). Mnemonic Descent Method: A Recurrent Process Applied for End-to-End Face Alignment. Proceedings of the Computer Vision and Pattern Recognition, Las Vegas, NV, USA.","DOI":"10.1109\/CVPR.2016.453"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Kowalski, M., Naruniec, J., and Trzcinski, T. (2017, January 21\u201326). Deep Alignment Network: A Convolutional Neural Network for Robust Face Alignment. Proceedings of the Computer Vision and Pattern Recognition Workshops, Honolulu, HI, USA.","DOI":"10.1109\/CVPRW.2017.254"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"372","DOI":"10.1109\/TPAMI.2011.112","article-title":"Toward a Practical Face Recognition System: Robust Alignment and Illumination by Sparse Representation","volume":"34","author":"Wagner","year":"2012","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Zhuang, L., Yang, A.Y., Zhou, Z., Sastry, S.S., and Ma, Y. (2013, January 23\u201328). Single-Sample Face Recognition with Image Corruption and Misalignment via Sparse Illumination Transfer. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Portland, OR, USA.","DOI":"10.1109\/CVPR.2013.455"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"272","DOI":"10.1007\/s11263-014-0749-x","article-title":"Sparse Illumination Learning and Transfer for Single-Sample Face Recognition with Image Corruption and Misalignment","volume":"114","author":"Zhuang","year":"2015","journal-title":"Int. J. Comput. Vis."},{"key":"ref_18","first-page":"8","article-title":"Extraction of symmetry properties using correlation with rotated and reflected images","volume":"76","author":"Masuda","year":"1993","journal-title":"Electron. Commun. Japan (Part III Fundam. Electron. Sci.)"},{"key":"ref_19","unstructured":"Liu, Y., Hays, J., Xu, Y.Q., and Shum, H.Y. (August, January 31). Digital papercutting. Proceedings of the ACM SIGGRAPH, Los Angeles, CA, USA."},{"key":"ref_20","first-page":"508","article-title":"Detecting symmetry and symmetric constellations of features","volume":"Volume 3952","author":"Loy","year":"2006","journal-title":"European Conference on Computer Vision"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"266","DOI":"10.1109\/TPAMI.2011.118","article-title":"Curved glide-reflection symmetry detection","volume":"34","author":"Lee","year":"2012","journal-title":"IEEE Trans. Pattern Anal. Mach. Intel."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Kondra, S., Petrosino, A., and Iodice, S. (2013, January 23\u201328). Multi-scale kernel operators for reflection and rotation symmetry: Further achievements. Proceedings of the Computer Vision and Pattern Recognition Workshops, Portland, OR, USA.","DOI":"10.1109\/CVPRW.2013.39"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Patraucean, V., Von Gioi, R.G., and Ovsjanikov, M. (2013, January 23\u201328). Detection of mirror-symmetric image patches. Proceedings of the Computer Vision and Pattern Recognition Workshops, Portland, OR, USA.","DOI":"10.1109\/CVPRW.2013.38"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Michaelsen, E., Muench, D., and Arens, M. (2013, January 23\u201328). Recognition of symmetry structure by use of gestalt algebra. Proceedings of the Computer Vision and Pattern Recognition Workshops, Portland, OR, USA.","DOI":"10.1109\/CVPRW.2013.37"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Cicconet, M., Geiger, D., Gunsalus, K.C., and Werman, M. (2014, January 23\u201328). Mirror symmetry histograms for capturing geometric properties in images. Proceedings of the Computer Vision and Pattern Recognition, Columbus, OH, USA.","DOI":"10.1109\/CVPR.2014.381"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Cai, D., Li, P., Su, F., and Zhao, Z. (2015, January 7\u201310). An adaptive symmetry detection algorithm based on local features. Proceedings of the Visual Communications and Image Processing Conference, Valletta, Malta.","DOI":"10.1109\/VCIP.2014.7051610"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1297","DOI":"10.1109\/TIP.2015.2393060","article-title":"Reflection symmetry detection using locally affine invariant edge correspondence","volume":"24","author":"Wang","year":"2015","journal-title":"IEEE Trans. Image Process."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1016\/j.patrec.2017.03.022","article-title":"A convolutional approach to reflection symmetry","volume":"95","author":"Cicconet","year":"2017","journal-title":"Pattern Recogn. Lett."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Funk, C., and Liu, Y. (2016, January 27\u201330). Symmetry reCAPTCHA. Proceedings of the Computer Vision and Pattern Recognition, Las Vegas, NV, USA.","DOI":"10.1109\/CVPR.2016.558"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1109\/TC.1972.5008923","article-title":"A Class of Algorithms for Fast Digital Image Registration","volume":"C-21","author":"Barnea","year":"1972","journal-title":"IEEE Trans. Comput."},{"key":"ref_31","first-page":"674","article-title":"An Iterative Image Registration Technique with an Application to Stereo Vision","volume":"81","author":"Lucas","year":"1981","journal-title":"Robotics"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1023\/B:VISI.0000011205.11775.fd","article-title":"Lucas\u2013Kanade 20 years on: A unifying framework","volume":"56","author":"Baker","year":"2004","journal-title":"Int. J. Comput. Vis."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"210","DOI":"10.1109\/TPAMI.2008.79","article-title":"Robust Face Recognition via Sparse Representation","volume":"31","author":"Wright","year":"2009","journal-title":"IEEE Trans. Pattern Anal. Mach. Intel."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"295","DOI":"10.1016\/S0262-8856(97)00070-X","article-title":"The FERET database and evaluation procedure for face-recognition algorithms","volume":"16","author":"Phillips","year":"1998","journal-title":"Image Vis. Comput."},{"key":"ref_35","unstructured":"Kanade, T., Cohn, J.F., and Yingli, T. (2000, January 21\u201323). Comprehensive database for facial expression analysis. Proceedings of the IEEE International Conference on Automatic Face and Gesture Recognition, Santa Barbara, CA, USA."}],"container-title":["Symmetry"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2073-8994\/11\/1\/96\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T12:26:28Z","timestamp":1760185588000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2073-8994\/11\/1\/96"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,1,16]]},"references-count":35,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2019,1]]}},"alternative-id":["sym11010096"],"URL":"https:\/\/doi.org\/10.3390\/sym11010096","relation":{},"ISSN":["2073-8994"],"issn-type":[{"type":"electronic","value":"2073-8994"}],"subject":[],"published":{"date-parts":[[2019,1,16]]}}}